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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

PANDEMIC: Occupancy driven predictive ventilation control to minimize energy consumption and infection risk

During the SARS-CoV-2 (COVID-19) pandemic, governments around the world have formulated policies requiring ventilation systems to operate at a higher outdoor fresh air flow rate for a sufficient time, which has led to a sharp increase in building energy consumption. Therefore, it is necessary to identify an energy-efficient ventilation strategy to reduce the risk of infection. In this study, we developed an occupant-number-based model predictive control (OBMPC) algorithm for building ventilation systems. First, we collected the occupancy and Heating, ventilation, and air conditioning system (HVAC) data from March to July 2021. Then, four different models (Auto regression moving average-based multilayer perceptron (ARMA_MLP), Recurrent neural networks (RNN), Long short-term memory networks (LSTM), and Nonhomogeneous Markov with change points detection (NH_Markov)) were used to predict the number of room occupants from 15 min to 24 h ahead with an interval output. We found that each model could predict the number of occupants with 85% accuracy using a one-person offset. Furthermore, the accuracy of 15 min of the ahead prediction could reach 95% with a one-person offset, but none of them could track abrupt changes. The occupancy prediction results were used to calculate the ventilation demand using the Wells-Riley equation, and the upper bound can maintain an infection risk lower than 2% for 93% of the day. This OBMPC model could reduce the coil load by 52.44% and shift the peak load by 3 h up to 5 kW compared with 24 × 7 h full outdoor air (OA) system when people wear masks in the space. The occupancy prediction uncertainty could cause a 9% to 26% difference in demand ventilation, a 0.3°C to 2.4°C difference in zone temperature, a 28.5% to 44.5% difference in outdoor airflow rate, and a 10.7% to 28.2% difference in coil load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Coverage-dependent structures and thermodynamic stability of intercalated Gd layers beneath buffer-layer graphene on SiC(0001)

Electronic properties of two-dimensional (2D) materials are strongly influenced by their atomic arrangements, making the theoretically-aided characterization of experimentally-synthesized 2D structures crucial. Using first-principles density functional theory, we analyze nearly 200 configurations of intercalated Gd layers beneath buffer-layer graphene on SiC(0001) over a Gd coverage range of 0.01 < θ < 1.2. By fully relaxing selectively-constructed configurations at each coverage within a large, low-strain supercell, we determine the coverage dependence of the chemical potential for intercalated Gd structures. Thermodynamically-preferred configurations below θ ≈ 0.8 form single-atom-thick monolayers, while 3D-like or multilayer structures emerge beyond θ ≈ 0.9. Most structures are amorphous-like, including the configuration at the chemical potential minimum around θ ≈ 0.4. In contrast, a strongly stretched Gd(0001)-like monolayer at θ = 1/3 and a nearly perfect Gd(0001) monolayer at θ = 1 are significantly less favorable with 0.16 eV and 0.82 eV higher chemical potentials above the minimum, respectively. Furthermore, the graphene layer decoupled by intercalated Gd near the chemical potential minimum is significantly flatter compared to its morphology above intercalated 3D structures at higher coverages and nearly isolated Gd atoms in the lowest coverage region. In conclusion, these findings align with our experimental results and underscore the need for further research on this unique intercalated system, which holds significant potential for diverse applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

All-alumina quarter-wave plate coatings fabricated by glancing angle deposition using serial bideposition

Anisotropic phase retarders, used in high power laser facilities to perform polarization smoothing, can be obtained by the glancing angle deposition (GLAD) coating process. Due to its high laser resistance, the coatings are mainly made of silica. Therefore, limited attention has been given to other dielectric materials. Here we present a study on alumina GLAD anisotropic coatings; a material with high laser resistance, higher birefringence and lower environmental sensitivity than silica. Since the anisotropy is related to the coatings microstructure through the deposition angle, samples were coated at angles varying from ± 68° to ± 82° using the serial bideposition technique. They were characterized by ellipsometry, polarimetry, spectrophotometry and electron microscopy. We showed that the highest birefringence is obtained at a deposition angle of ± 76° with an in-plane value of 0.053. Based on these results, a quarter-wave plate at 351 nm was designed as a multilayer with seven pairs of anisotropic layers deposited at ± 76° and isotropic layers deposited at 0°. The fabricated coating exhibited a uniform retardance of 88.51 ± 0.45 nm. The alumina GLAD wave plates presented here, open the door to new possibilities in the laser field and especially in the field of fusion energy.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Molecular dynamics simulations of stratum corneum lipid mixtures: A multiscale perspective

The lipid matrix of the stratum corneum (SC) layer of skin is essential for human survival; it acts as a barrier to prevent rapid dehydration while keeping potentially hazardous material outside the body. While the composition of the SC lipid matrix is known, the molecular-level details of its organization are difficult to infer experimentally, hindering the discovery of structure-property relationships. To this end, molecular dynamics simulations, which give molecular-level resolution, have begun to play an increasingly important role in understanding these relationships. Furthermore, most simulation studies of SC lipids have focused on preassembled bilayer configurations, which, owing to the slow dynamics of the lipids, may influence the final structure and hence the calculated properties. Self-assembled structures would avoid this dependence on the initial configuration, however, the size and length scales involved make self-assembly impractical to study with atomistic models. Here, we report on the development of coarse-grained models of SC lipids designed to study self-assembly. Building on previous work, we present the interactions between the headgroups of ceramide and free fatty acid developed using the multistate iterative Boltzmann inversion method. Validation of the new interactions is performed with simulations of preassembled bilayers and good agreement between the atomistic and coarse-grained models is found for structural properties. The self-assembly of mixtures of ceramide and free fatty acid is investigated and both bilayer and multilayer structures are found to form. This work therefore represents a necessary step in studying SC lipid systems on multiple time and length scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
DOE OSTI2023

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Electric current control of creation and annihilation of sub-100 nm magnetic bubbles examined by full-field transmission soft X-ray microscopy

The effect of electric current pulses on a sub-100 nm magnetic bubble state in a symmetric Pt/Co multilayer was directly observed using a full-field transmission soft X-ray microscope (MTXM). Field-induced evolution of the magnetic stripe domains into isolated bubbles with their sizes down to 100 nm was imaged under varying external magnetic fields. Electric current pulses were then applied to the created magnetic bubbles, and it was observed that the bubbles could be either created or annihilated by the current pulse depending on the strength of applied magnetic field. The results suggest that the Joule heating plays a critical role in the formation and/or elimination of the bubbles and skyrmions. Finally, the schematic phase diagram for the creation and annihilation of bubbles is presented, suggesting an optimized scheme with the combination of magnetic field and electric current necessary to utilize skyrmions in the practical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Bottom up synthesis of boron-doped graphene for stable intermediate temperature fuel cell electrodes

The high surface area and electrical conductivity of few-layered graphene would make it an ideal catalyst support and electrode in fuel cells apart from its susceptibility to oxidative corrosion. Here we report the single-step, bottom-up synthesis of oxidation-resistant boron-doped graphene and show its increased stability in the aggressive electrochemical environment of intermediate temperature solid acid fuel cells (SAFCs). Boron was shown to alter the growth mode of single walled carbon nanohorns by laser vaporization to produce high yields of thin (<20 layer) boron-doped (2–3 at.%) crystalline flakes of turbostratic graphene (B-GLF). Alternatively, adding partial pressures of hydrogen less effectively shifted the growth mode of SWCNHs toward planar, turbostratic graphene-like flakes (GLFs). Thermogravimetric analysis indicates that boron-doping enhances the oxidation resistance of few-layer GLFs by >140 °C, with large fractions of multilayered B-GLFs surviving 10 °C/min ramps to 1000 °C. These B-GLFs provided a stable Pt catalyst support and electrode over 40 h operation in SAFCs with cesium dihydrogen phosphate electrolyte operating at 250 °C, as opposed to undoped GLFs or SWCNHs which were nearly completely consumed. Furthermore, the facile synthesis and oxidation-resistant properties of boron-doped GLF appear promising for graphene applications in oxidizing environments.

25 ENERGY STORAGE↗
DOE OSTI2019

Orders of magnitude reduction in the thermal conductivity of polycrystalline diamond through carbon, nitrogen, and oxygen ion implantation

Despite the exceptional thermal and mechanical functionalities of diamond, its superlative properties are highly subject to the presence of point defects, dislocations, and interfaces. Here, polycrystalline diamond is ion implanted with C 3+ , N 3+ , and O 3+ ions at an energy of 16.5 MeV, producing an amorphous layer at the projected range and a damaged crystalline region between the surface and amorphous layer. Using time-domain thermoreflectance in combination with thermal penetration depth calculations based upon the multilayer heat diffusion equation, it is determined that reductions in the thermal conductivity can span nearly two orders of magnitude while still maintaining a polycrystalline structure within the regions thermally probed. Dynamical diffraction simulations of high-resolution x-ray diffraction measurements demonstrate the formation of a strained layer localized at the end of range, with much lower levels of strain near the surface. Furthermore, within the polycrystalline region above the amorphous layer, the average number of displacements-per-atom from the ion irradiation is found to be < 1%, with mass impurity concentrations much less than 1%. These low defect concentrations within the thermally probed region demonstrate the remarkably large impact that dilute levels of defects from the ion implantation can have on the thermal conductivity of diamond.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Diethylenetriamine-functionalized graphene oxide: Insights into ion adsorption and applications in rare earth element separation

The growing demand for critical minerals and materials requires atom- and energy-efficient, selective separations to overcome the challenges posed by the similar chemical and physical properties of the rare earth elements (REEs) and their low concentrations in unconventional domestic feedstocks. Here, in this study, we developed diethylenetriamine-functionalized graphene oxide (DETA-GO) as a membrane material for REE adsorption and separation. Synthesis conditions were optimized to maximize nitrogen incorporation while also preserving GO dispersibility for facile membrane fabrication. We investigated the mechanism of amine functionalization, the nitrogen-bonding configurations, the organization of the interlayer transport channels, and the resulting effects on ion and water transport for REE separations. Neat-GO and DETA-GO multilayer laminate membranes were fabricated by vacuum filtration onto polymer supports. To investigate the effects of amine functionalization, the membranes were characterized using scanning electron microscopy, Raman, Fourier transform infrared, and X-ray photoelectron spectroscopy, as well as grazing-incidence X-ray diffraction measurements. Ion permeation experiments with representative lanthanum (La 3+ ) and ytterbium (Yb 3+ ) solutions revealed enhanced ion adsorption and water transport through DETA-GO membranes compared to neat-GO. The strong affinity of the membranes for multivalent REEs was also validated with conductivity and inductively coupled plasma mass spectrometry measurements. Atomistic insight into the role of amine functionalization in modulating nanochannel architecture and long-term stability, optimizing adsorption sites, and regulating REE and water transport was obtained using classical molecular dynamics simulations. Collectively, our joint experimental and theoretical study demonstrates the potential of DETA-GO membranes for selective REE separations, offering insights into ion-binding mechanisms, water-transport properties, and nanochannel optimization for the recovery of critical materials from aqueous feedstocks.

Adsorbent↗
DOE OSTI2019

Nacre-inspired hemicelluloses paper with fire retardant and gas barrier properties by self-assembly with bentonite nanosheets

A need for fabricating robust hemicelluloses composites has been continuously gaining ground so as to replace petroleum-derived materials with renewable resources. Here, a new galactomannan with high molecular weight was extracted from endosperms of Sesbania cannabina which could improve the formation of arabinoxylan film. Inspired by the excellent mechanical properties and hierarchical structure of natural nacre, these naturally extracted arabinoxylan and galactomannan were further self-assembled with bentonite nanosheets, generating a ternary paper with multilayered structure. These hemicelluloses-bentonite papers exhibited the highest tensile strength of 80.87 MPa, 2.39 times that of the hemicelluloses paper without bentonite, which was achieved by the crosslinking reactions between hemicelluloses and bentonite nanosheets. Our study further reflected that these papers possess superior gas barrier, water-resistant and fire-retardant properties with the addition of small amount of bentonite nanosheet, which holds the potential for use as fire-protective insulations, coatings, packaging, and aerospace materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The phage nucleus synergizes with an anti-defense protein to resist bacterial immunity

Chimallivirus bacteriophages enclose their replicating genomes in a protein-based compartment termed the phage nucleus. While the phage nucleus segregates phage DNA from host immune proteins, it is not known if additional factors are required to protect against DNA-targeting host defenses. Here, we identify a chimallivirus-encoded DarG2-like antitoxin that localizes to the phage nucleus and provides protection against phage-targeting DarTG2 toxin-antitoxin systems. This protein, which we term AdfM (anti-darT factor macro), contains a macrodomain and removes DarT2-mediated ADP-ribose modifications from DNA. In the absence of AdfM, DarT2 modifies phage DNA and restricts chimallivirus replication despite being largely excluded from the phage nucleus. Increasing the nuclear concentration of DarT2 while decreasing the nuclear concentration of AdfM reduces phage replication. These results show that the phage nucleus is insufficient to completely protect the chimallivirus genome from host defenses; rather, it is one component of a multilayered counter-defense strategy.

CRISPR↗
DOE OSTI2025

Measuring the flatband potential in 2D semiconductors: Pitfalls and a possible SECCM solution

The flatband potential (V fb ) is a critical parameter in semiconductor electrochemistry, defining the potential at which no excess charge exists at the semiconductor/electrolyte interface. It serves as a key reference for interpreting charge transfer kinetics and current–voltage behavior. However, conventional methods like Mott–Schottky analysis fail for atomically thin 2D materials due to the breakdown of the depletion approximation. This perspective examines the limitations of traditional V fb measurements for 2D semiconductors and the experimental challenges that arise. To address these issues, we propose using scanning electrochemical cell microscopy (SECCM) to spatially resolve the potential of zero charge (V pzc ), equivalent to V fb . This approach mitigates sample heterogeneity issues, such as pinholes or multilayer defects, and offers a pathway to more accurate electrochemical characterization. Ultimately, this method will enhance understanding of current–potential behavior in 2D materials, supporting the design of advanced systems for photoelectrocatalysis, energy conversion, and sensing.

2D semiconductors↗
DOE OSTI2019

Critical operating stress of persistent slip bands in Cu

This work elucidates the dependence of operating stress of persistent slip bands (PSB) on the channel width and wall dislocation density. Using Cu as a model system and molecular dynamics as the main investigative tool, a new length scale effect, namely the wall dislocation spacing, is provided to enhance theoretical understanding of PSBs. It is discovered that the operation of PSB is a thermally activated event in which operating stress is inversely related to the wall dislocation spacing, strain rate and temperature. Leveraging the existing framework of confined layer slip in nanoscale metallic multilayers and classical nucleation theory, a mathematical model describing the rate- and temperature- dependent PSB operating stress is here proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. Here, an extension to the time–temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time–temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process–microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process–microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Computational study on the removal of photolabile protecting groups by photochemical reactions

The application and versatility of photolabile protecting groups (PPGs) have continued to expand since their inception almost 50 years ago. Here, in the present work we employ density functional theory (DFT) to characterize ground and excited state properties of several compounds with PPGs and to explore possible, controllable photodissociation reactions that remove these PPGs. The reaction mechanism is examined by analyzing the DFT results as well as dynamical simulations of nonadiabatic electron transfer reactions using multilayer multiconfiguration time-dependent Hartree theory. The photoexcited compounds appear to undergo ultrafast back electron transfer to the ground electronic state via internal conversion. For some compounds, the electronic-nuclear couplings facilitate sufficient photo energy transfer to the nuclear degrees of freedom that dominate the reaction coordinate, leading to the dissociation reaction that removes the PPGs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments

We present that x-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materials research. Such data require for their analysis a structure optimization process comparing experiment to theory that is not straightforward. In this work, we present a new computer program for optimizing the analysis of standing-wave data, called SWOPT, that automates this trial-and-error optimization process. The program includes an algorithm that has been developed for computationally expensive problems: so-called black-box simulation optimizations. It also includes a more efficient version of the Yang X-ray Optics Program (YXRO) [Yang, S.-H., Gray, A.X., Kaiser, A.M., Mun, B.S., Sell, B.C., Kortright, J.B., Fadley, C.S., J. Appl. Phys. 113, 1 (2013)] which is about an order of magnitude faster than the original version. Human interaction is not required during optimization. We tested our optimization algorithm on real and hypothetical problems and show that it finds better solutions significantly faster than a random search approach. The total optimization time ranges, depending on the sample structure, from minutes to a few hours on a modern laptop computer, and can be up to 100x faster than a corresponding manual optimization. Finally, these speeds make the SWOPT program a valuable tool for realtime analyses of data during synchrotron experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhancing EnergyPlus capabilities to model dynamic building envelopes using python plugin

Nearly half of the energy consumption in the United States is related to buildings, resulting in an urgent need to develop innovative technologies to improve building energy efficiency. Dynamic building envelopes, comprising switchable insulation and thermal energy storage materials, have been proposed recently as a promising solution to reduce buildings' heating and cooling loads by thermally coupling the indoor environment with the ambient environment when beneficial while decoupling them when outdoor conditions are not favorable. Although various related technologies are still underway, the whole-building energy modeling tools, like EnergyPlus, do not have the capability to simulate the transient and dynamic nature of dynamic envelope materials and components to accurately predict their impact on building energy use. The objective of this study is to formulate a method in EnergyPlus simulation engine to model multilayer envelopes, comprising dynamic building materials with variable thermophysical properties, and discuss the changes made to the program using a Python plugin. Furthermore, the thermal performance of the dynamic envelopes using the proposed method is compared and verified with the results from a well-established commercial code, COMSOL Multiphysics. A parametric assessment is also conducted to evaluate the energy efficiency benefits of dynamic envelopes in a single-family residential building, demonstrating total annual energy savings up to 11.6 %, when a dynamic envelope operates alone, and up to 18.2 % when it is combined with a thin layer of phase change material as a thermal storage medium. Finally, a United States wide energy efficiency assessment is presented to showcase the geographical spread of the energy savings. The method designed and implemented in this study provides the researchers with the ability to implement their dynamic insulation methods in EnergyPlus and evaluate the whole building energy impact.

25 ENERGY STORAGE↗